High-performance cone beam reconstruction using CUDA compatible GPUs

Compute unified device architecture (CUDA) is a software development platform that allows us to run C-like programs on the nVIDIA graphics processing unit (GPU). This paper presents an acceleration method for cone beam reconstruction using CUDA compatible GPUs. The proposed method accelerates the Feldkamp, Davis, and Kress (FDK) algorithm using three techniques: (1) off-chip memory access reduction for saving the memory bandwidth; (2) loop unrolling for hiding the memory latency; and (3) multithreading for exploiting multiple GPUs. We describe how these techniques can be incorporated into the reconstruction code. We also show an analytical model to understand the reconstruction performance on multi-GPU environments. Experimental results show that the proposed method runs at 83% of the theoretical memory bandwidth, achieving a throughput of 64.3 projections per second (pps) for reconstruction of 512³-voxel volume from 360 512²-pixel projections. This performance is 41% higher than the previous CUDA-based method and is 24 times faster than a CPU-based method optimized by vector intrinsics. Some detailed analyses are also presented to understand how effectively the acceleration techniques increase the reconstruction performance of a naive method. We also demonstrate out-of-core reconstruction for large-scale datasets, up to 1024³-voxel volume.     

A New Monte Carlo Method for Evaluating System-Failure Probability

This paper proposes, under a rare-event assumption, a new ``Coverage Monte Carlo' method for evaluating the top-event probability of a coherent fault tree. All the min cuts are assumed to be known. A Karp-Luby Monte Carlo (KLM) estimator with minimum variance is derived in a different manner. The KLM evaluates an inclusion-exclusion formula excluding the first sum of products. A new coverage Monte Carlo (NCM) estimator evaluates the formula excluding the first and the second sums of products. The NCM yields an estimator with a smaller variance than the KLM which becomes a linear time procedure in the number of min cuts. Upper bounds on the numbers of trials necessary to attain a given coefficient of variation are derived for KLM and NCM. The bounds can be calculated before any Monte Carlo trials. The KLM requires at least 8 times more trials than the NCM. Given sufficient computer memory to implement an alias sampling method, the NCM requires less computation time than the KLM when an accurate estimate is required. The NCM is more favorable when the deterministic bounding practice based on the first and second sums of products yields a smaller relative error. The NCM is consistent with the fact that deterministic bounds have been computed.     

Analysis for optimum threshold voltage and load current of E-D-type GaAs DCFL circuits

A GaAs MESFET E-D invertor was analysed to estimate the optimum threshold voltage VT for a switching FET, and the optimum load current IL for a load FET, that will minimise the invertor switching time. The calculated results show that the optimum VT lies at around 0.2 V, and the optimum IL is about 55% of the saturation current of the switching FET.     

Influences of nonuniformity in metal concentration in gate dielectric silicate on CMIS inverters'' propagation delay time

It is shown that propagation delay time in CMIS (complementary metal insulator semiconductor field effect transistor) inverters is strongly affected by dielectric constant nonuniformity in gate dielectrics caused by the phase separation in silicate films. Influences of such nonuniformity on load capacitance are studied by analytical calculations based on a physical model which takes polarization into account. It is newly found that load capacitances are affected by the phase separation in qualitatively different ways, depending on the average metal concentration of their dielectric films. An experimental result is compared with those calculations. Influences of such nonuniformity on current drivability are studied by 3-dimensional device simulations. It is also newly found that such nonuniformity affects load capacitance and current drivability in different ways, resulting in an increase in propagation delay time of CMIS inverters for all metal concentrations studied. An explanation of this phenomenon is given with physical considerations.     

Precipitation phenomena in and electrical resistivity of high-temperature treated langatate (La3Ta0.5Ga5.5O14)

La(3)Ta(0.5)Ga(5.5)O(14) (LTG) single crystals, which have no phase transition up to the melting point, were heat-treated in air at temperatures from 1000°C to 1450°C for 10 h. LaTaO(4) (LT) and LaGaO(3) (LG), which coexist with LTG in the three-phase region on the Ga-poor side, precipitated on the surface of the crystal for heat treatments above 1300°C because of Ga evaporation during the heat treatment. The Ga-poor state near the surface of the 1450°C heat-treated specimen was confirmed by electron probe micro-analysis measurements. The electrical resistivity of LTG single crystals decreased by heat treatment in the range of 1000°C to 1200°C for 10 h in air, where no precipitation was observed, whereas the resistivity increased with heat treatment over 1400°C for 10 h in air. The electrical resistivity of the Ga-poor surface region was higher than that of the interior.     

Radioactivation of structural material of the superconducting magnet for a fusion reactor

Radioactivation of five types of candidate steel alloys for the structural materials of superconducting toroidal field coils (TFC) of a D-T fusion reactor has been comparatively studied. As a result, the use of a high Mn steel in place of 316 SS is shown to reduce the dose rate at the He vessel of the TFC to ～ 1/3 the value with 316 SS at 1 day after shutdown, and to ～ 1/1000 at 10 years after shutdown. These reductions are mostly caused by the 0.28 wt% Co assumed to be included in 316 SS but none in the high Mn steel. Newly defined dose rate sensitivities of constituent elements are shown to be useful in identifying the cause of dose rate change brought on by the steel composition change. They can also be utilized in estimating the dose rate change brought on by the replacement of 316 SS with any new steel alloy with similar composition.     

An algorithm for improving the reliability of detection with processing of multiple sensors''signal

Recent surveys show that most of the false alarms of fire alarm systems are given by deceptive phenomena caused by human actions, such as cigarette smoking and cooking. Software-controlled systems have a potential ability in increasing the reliability of detection signals by data processing. However, it is rather difficult to distinguish an early stage fire from those deceptive phenomena only by processing the data of a single sensor. The authors' new algorithm utilizes the signals from three different sensors, i.e. temperature, smoke and gas (CO) concentration. Incorporating a mathematical fire model, these signals are translated into source parameters such as heat release rate, and smoke and gas generation rates. The conditions of the fire are then analyzed using the cross-correlation function between these source parameters. Testing the algorithm has been done using some experimental data and a promising result has been obtained.